Abstract
This chapter summarizes the extant sociological literature on the interactive nature of school and teacher effects on student learning. It explains why the most recent literature on teacher sorting demands the attention of more sociologists of education, and it demonstrates what is revealed about patterns of teacher sorting using the type of data most commonly analyzed by sociologists of education. Throughout, the chapter discusses the methodological requirements of research that can and cannot disentangle teacher effects from school effects, and it considers how teacher and school effects may be evolving in the changing landscape of K–12 education in the United States.
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Notes
- 1.
For the specific numbers, see Tables 6a and 6b, pages 16–17, Tables 2.31.5 and 2.31.6, pages 124–25, Tables 2.33.1–8, pages 131–40, Tables 2.34.1–14, pages 149–62.
- 2.
And such studies have continued. Crosnoe et al. (2004), for example, offer evidence of more general achievement gains that result from healthy relationships between students and teachers, which they measure as intergenerational bonding. Now, economists are very much interested in such effects, as we discuss below.
- 3.
The recent economics literature, which has leveraged administrative data sources, is also relevant, especially for the claim of match effects. Egalite et al. (2015), for example, show that in Florida the race congruence of student–teacher pairing promotes small but positive effects, even though Winters et al. (2013) argue that gender congruence appears to have no substantial effects. See also Jackson (2013) for a broad treatment of teacher match effects, which demonstrates their importance with empirical results from North Carolina.
- 4.
The economics literature is also consistent with the skills claim. Ehrenberg and Brewer (1994), analyzing the High School and Beyond data, show that teachers’ degrees have positive associations with achievement, perhaps indicating that teacher ability is important. More recently, Clotfelter et al. (2007), through an analysis of North Carolina administrative data, show that teacher experience, test scores, and licensure all have positive associations with achievement, although more for math than for reading. Kukla-Acevedo (2009) show that in a Kentucky school district teachers’ math preparation predicted fifth grade math achievement.
- 5.
We do not mean to imply that scholars did not study assignment and sorting patterns before the era of accountability arrived in the 1990s. One early careful study in sociology is Becker (1952a), as summarized above. And, in the wake of EEO, and after the U.S. Supreme Court ruled that racial balance in the teaching corps is a measure of unitary status in desegregating school districts, scholars became very much interested in the distribution of teachers across schools in the same area. For example, Greenberg and McCall (1974) show that in the San Diego school system teachers sorted across schools based on the socioeconomic status of students, given that the salaries available did not differ across the district. Studies such as this one led to deeper modeling of teachers’ revealed preferences and the possibilities for interventions to change their job search choices (see Antos and Rosen 1975; Levinson 1988).
- 6.
For clear, simple, accurate, and balanced summaries of value-added modeling, see Corcoran and Goldhaber (2013) and Corcoran (2016). To understand the required assumptions with more depth, see Reardon and Raudenbush (2009). For studies that have defended and deployed VAMs, see Chetty et al. (2014a, b). For arguments against the use of VAMs, see Rothstein (2009, 2010) and Guarino, Reckase, Wooldridge (2015). For work that compares the results of VAMs to various other types of teacher evaluation systems, see Grissom and Youngs (2016).
- 7.
Jacob and Lefgren (2007) show that parents disproportionately prefer effective teachers in high poverty schools, perhaps because such teachers are comparatively rare.
- 8.
Our analysis is related to, but distinct from, the most common prior analyses of national distributions of teachers. These prior studies, which have been discussed above, have frequently used the Schools and Staffing Surveys (SASS). Analysis of the SASS surveys allows for the modeling of teacher distributions across schools, but not directly of teacher distributions across students, since only school aggregate measures of student characteristics are available, and typically without detailed measures of the family backgrounds of students.
- 9.
On average, we have 4.4 sampled students for each math teacher and 5.4 sampled students for each science teacher, with medians of 3 and 4 students, respectively. At the school level, the median number of math teachers is 4 across the 720 schools with sampled math teachers while the median number of science teachers is 3 across the 699 schools with sampled science teachers.
- 10.
We exclude private schools from this analysis, mostly because the teacher sorting literature is very much focused on public schools. Of course, teachers do sort into private schools as well, and private schools have served as a valuable point of comparison in the effective schools research in sociology. A more comprehensive analysis should consider sorting by sector and type of school as well.
- 11.
These within-school scales of SES also have more measurement error, and so the correlation coefficients are further attenuated. Notice also that we do have meaningful but very small negative partial correlation coefficients for within-school SES with the student and parent attitude, behavior, and support scales. These coefficients suggest that there is a very slight tendency for teachers who are assigned to lower-SES students within their schools to report more challenges created by the attitudes and behavior of students and parents.
- 12.
In the supplementary appendix, we offer four analogous tables (S1 through S4) for the 10-state saturated sample of schools in the HSLS. For the results reported in these additional tables, we include fixed effects for states in the underlying regression models. The results presented there demonstrate that the average within-state partial correlation coefficients are only slightly smaller in magnitude in nearly all cases of direct comparison to those in Tables 23.1 through 23.4, suggesting that these weak patterns of teacher sorting are characteristic of within-state relationships as well. This result implies, even though it is based on an analysis of only 10 states, that the weakness of the associations is not generated by suppression that is attributable to unspecified state-level differences in the results in Tables 23.1 through 23.4.
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Morgan, S.L., Shackelford, D.T. (2018). School and Teacher Effects. In: Schneider, B. (eds) Handbook of the Sociology of Education in the 21st Century. Handbooks of Sociology and Social Research. Springer, Cham. https://doi.org/10.1007/978-3-319-76694-2_23
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